abydos.phonetic._bmpm._bm_phonetic() - Code Metrics - Inspection of "78a222a9f7d8976f6744d263e3d6d01a2a991c27" - chrislit/abydos - Measure and Improve Code Quality continuously with Scrutinizer

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Branch — master (78a222)

by Chris
created 2018-10-26 11:30 UTC
abydos.phonetic._bmpm._bm_phonetic() F

↳ Parent: abydos.phonetic._bmpm
Complexity

Conditions
Size

Total Lines	160
Code Lines	91
Duplication

Lines	0
Ratio	0 %
Code Coverage

Tests	61
CRAP Score	23
Importance

Changes
Metric	Value
eloc	91
dl	0
loc	160
ccs	61
cts	61
cp	1
rs	0
c	0
b	0
f	0
cc	23
nop	7
crap	23
How to fix Long Method Complexity

# -*- coding: utf-8 -*-

# Copyright 2014-2018 by Christopher C. Little.
# This file is part of Abydos.
#
# This file is based on Alexander Beider and Stephen P. Morse's implementation
# of the Beider-Morse Phonetic Matching (BMPM) System, available at
# http://stevemorse.org/phonetics/bmpm.htm.
#
# Abydos is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Abydos is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Abydos. If not, see <http://www.gnu.org/licenses/>.

"""abydos.phonetic._bmpm.

The phonetic._bmpm module implements the Beider-Morse Phonentic Matching (BMPM)
algorithm.
"""

from __future__ import unicode_literals

from re import search
from unicodedata import normalize

from six import PY3, text_type
from six.moves import range

from ._bmdata import (
    BMDATA,
    L_ANY,
    L_ARABIC,
    L_CYRILLIC,
    L_CZECH,
    L_DUTCH,
    L_ENGLISH,
    L_FRENCH,
    L_GERMAN,
    L_GREEK,
    L_GREEKLATIN,
    L_HEBREW,
    L_HUNGARIAN,
    L_ITALIAN,
    L_LATVIAN,
    L_NONE,
    L_POLISH,
    L_PORTUGUESE,
    L_ROMANIAN,
    L_RUSSIAN,
    L_SPANISH,
    L_TURKISH,
)

__all__ = ['bmpm']

if PY3:
    long = int


_LANG_DICT = {
    'any': L_ANY,
    'arabic': L_ARABIC,
    'cyrillic': L_CYRILLIC,
    'czech': L_CZECH,
    'dutch': L_DUTCH,
    'english': L_ENGLISH,
    'french': L_FRENCH,
    'german': L_GERMAN,
    'greek': L_GREEK,
    'greeklatin': L_GREEKLATIN,
    'hebrew': L_HEBREW,
    'hungarian': L_HUNGARIAN,
    'italian': L_ITALIAN,
    'latvian': L_LATVIAN,
    'polish': L_POLISH,
    'portuguese': L_PORTUGUESE,
    'romanian': L_ROMANIAN,
    'russian': L_RUSSIAN,
    'spanish': L_SPANISH,
    'turkish': L_TURKISH,
}

BMDATA['gen']['discards'] = {
    'da ',
    'dal ',
    'de ',
    'del ',
    'dela ',
    'de la ',
    'della ',
    'des ',
    'di ',
    'do ',
    'dos ',
    'du ',
    'van ',
    'von ',
    'd\'',
}
BMDATA['sep']['discards'] = {
    'al',
    'el',
    'da',
    'dal',
    'de',
    'del',
    'dela',
    'de la',
    'della',
    'des',
    'di',
    'do',
    'dos',
    'du',
    'van',
    'von',
}
BMDATA['ash']['discards'] = {'bar', 'ben', 'da', 'de', 'van', 'von'}

# format of rules array
_PATTERN_POS = 0
_LCONTEXT_POS = 1
_RCONTEXT_POS = 2
_PHONETIC_POS = 3


def _bm_language(name, name_mode):
    """Return the best guess language ID for the word and language choices.

    :param str name: the term to guess the language of
    :param str name_mode: the name mode of the algorithm: 'gen' (default),
                'ash' (Ashkenazi), or 'sep' (Sephardic)
    """
    name = name.strip().lower()
    rules = BMDATA[name_mode]['language_rules']
    all_langs = sum(_LANG_DICT[_] for _ in BMDATA[name_mode]['languages']) - 1
    choices_remaining = all_langs
    for rule in rules:
        letters, languages, accept = rule
        if search(letters, name) is not None:
            if accept:
                choices_remaining &= languages
            else:
                choices_remaining &= (~languages) % (all_langs + 1)
    if choices_remaining == L_NONE:
        choices_remaining = L_ANY
    return choices_remaining


def _bm_redo_language(

    term, name_mode, rules, final_rules1, final_rules2, concat

):
    """Reassess the language of the terms and call the phonetic encoder.

    Uses a split multi-word term.

    :param str term: the term to encode via Beider-Morse
    :param str name_mode: the name mode of the algorithm: 'gen' (default),
        'ash' (Ashkenazi), or 'sep' (Sephardic)
    :param tuple rules: the set of initial phonetic transform regexps
    :param tuple final_rules1: the common set of final phonetic transform
        regexps
    :param tuple final_rules2: the specific set of final phonetic transform
        regexps
    :param bool concat: a flag to indicate concatenation
    """
    language_arg = _bm_language(term, name_mode)
    return _bm_phonetic(
        term,
        name_mode,
        rules,
        final_rules1,
        final_rules2,
        language_arg,
        concat,
    )


def _bm_phonetic(

    term,

    name_mode,

    rules,

    final_rules1,

    final_rules2,

    language_arg=0,

    concat=False,

):
    """Return the Beider-Morse encoding(s) of a term.

    :param str term: the term to encode via Beider-Morse
    :param str name_mode: the name mode of the algorithm: 'gen' (default),
        ash' (Ashkenazi), or 'sep' (Sephardic)
    :param tuple rules: the set of initial phonetic transform regexps
    :param tuple final_rules1: the common set of final phonetic transform
        regexps
    :param tuple final_rules2: the specific set of final phonetic transform
        regexps
    :param int language_arg: an integer representing the target language of the
        phonetic encoding
    :param bool concat: a flag to indicate concatenation
    """
    term = term.replace('-', ' ').strip()

    if name_mode == 'gen':  # generic case
        # discard and concatenate certain words if at the start of the name
        for pfx in BMDATA['gen']['discards']:
            if term.startswith(pfx):
                remainder = term[len(pfx) :]
                combined = pfx[:-1] + remainder
                result = (
                    _bm_redo_language(
                        remainder,
                        name_mode,
                        rules,
                        final_rules1,
                        final_rules2,
                        concat,
                    )
                    + '-'
                    + _bm_redo_language(
                        combined,
                        name_mode,
                        rules,
                        final_rules1,
                        final_rules2,
                        concat,
                    )
                )
                return result

    words = term.split()  # create array of the individual words in the name
    words2 = []

    if name_mode == 'sep':  # Sephardic case
        # for each word in the name, delete portions of word preceding
        # apostrophe
        # ex: d'avila d'aguilar --> avila aguilar
        # also discard certain words in the name

        # note that we can never get a match on "de la" because we are checking
        # single words below
        # this is a bug, but I won't try to fix it now

        for word in words:
            word = word[word.rfind('\'') + 1 :]
            if word not in BMDATA['sep']['discards']:
                words2.append(word)

    elif name_mode == 'ash':  # Ashkenazic case
        # discard certain words if at the start of the name
        if len(words) > 1 and words[0] in BMDATA['ash']['discards']:
            words2 = words[1:]
        else:
            words2 = list(words)
    else:
        words2 = list(words)

    if concat:
        # concatenate the separate words of a multi-word name
        # (normally used for exact matches)
        term = ' '.join(words2)
    elif len(words2) == 1:  # not a multi-word name
        term = words2[0]
    else:
        # encode each word in a multi-word name separately
        # (normally used for approx matches)
        result = '-'.join(
            [
                _bm_redo_language(
                    w, name_mode, rules, final_rules1, final_rules2, concat
                )
                for w in words2
            ]
        )
        return result

    term_length = len(term)

    # apply language rules to map to phonetic alphabet
    phonetic = ''
    skip = 0
    for i in range(term_length):
        if skip:
            skip -= 1
            continue
        found = False
        for rule in rules:
            pattern = rule[_PATTERN_POS]
            pattern_length = len(pattern)
            lcontext = rule[_LCONTEXT_POS]
            rcontext = rule[_RCONTEXT_POS]

            # check to see if next sequence in input matches the string in the
            # rule
            if (pattern_length > term_length - i) or (
                term[i : i + pattern_length] != pattern

            ):  # no match
                continue

            right = '^' + rcontext
            left = lcontext + '$'

            # check that right context is satisfied
            if rcontext != '':
                if not search(right, term[i + pattern_length :]):
                    continue

            # check that left context is satisfied
            if lcontext != '':
                if not search(left, term[:i]):
                    continue

            # check for incompatible attributes
            candidate = _bm_apply_rule_if_compat(
                phonetic, rule[_PHONETIC_POS], language_arg
            )
            # The below condition shouldn't ever be false
            if candidate is not None:  # pragma: no branch
                phonetic = candidate
                found = True
                break

        if not found:  # character in name that is not in table -- e.g., space
            pattern_length = 1
        skip = pattern_length - 1


    # apply final rules on phonetic-alphabet,
    # doing a substitution of certain characters
    phonetic = _bm_apply_final_rules(
        phonetic, final_rules1, language_arg, False
    )  # apply common rules
    # final_rules1 are the common approx rules,
    # final_rules2 are approx rules for specific language
    phonetic = _bm_apply_final_rules(
        phonetic, final_rules2, language_arg, True
    )  # apply lang specific rules

    return phonetic


def _bm_apply_final_rules(phonetic, final_rules, language_arg, strip):

    """Apply a set of final rules to the phonetic encoding.

    :param str phonetic: the term to which to apply the final rules
    :param tuple final_rules: the set of final phonetic transform regexps
    :param int language_arg: an integer representing the target language of the
        phonetic encoding
    :param bool strip: flag to indicate whether to normalize the language
        attributes
    """
    # optimization to save time
    if not final_rules:
        return phonetic

    # expand the result
    phonetic = _bm_expand_alternates(phonetic)
    phonetic_array = phonetic.split('|')

    for k in range(len(phonetic_array)):

        phonetic = phonetic_array[k]
        phonetic2 = ''
        phoneticx = _bm_normalize_lang_attrs(phonetic, True)

        i = 0
        while i < len(phonetic):
            found = False

            if phonetic[i] == '[':  # skip over language attribute
                attrib_start = i
                i += 1
                while True:
                    if phonetic[i] == ']':
                        i += 1
                        phonetic2 += phonetic[attrib_start:i]
                        break
                    i += 1
                continue

            for rule in final_rules:
                pattern = rule[_PATTERN_POS]
                pattern_length = len(pattern)
                lcontext = rule[_LCONTEXT_POS]
                rcontext = rule[_RCONTEXT_POS]

                right = '^' + rcontext
                left = lcontext + '$'

                # check to see if next sequence in phonetic matches the string
                # in the rule
                if (pattern_length > len(phoneticx) - i) or phoneticx[
                    i : i + pattern_length

                ] != pattern:
                    continue

                # check that right context is satisfied
                if rcontext != '':
                    if not search(right, phoneticx[i + pattern_length :]):
                        continue

                # check that left context is satisfied
                if lcontext != '':
                    if not search(left, phoneticx[:i]):
                        continue

                # check for incompatible attributes
                candidate = _bm_apply_rule_if_compat(
                    phonetic2, rule[_PHONETIC_POS], language_arg
                )
                # The below condition shouldn't ever be false
                if candidate is not None:  # pragma: no branch
                    phonetic2 = candidate
                    found = True
                    break

            if not found:
                # character in name for which there is no substitution in the
                # table
                phonetic2 += phonetic[i]
                pattern_length = 1

            i += pattern_length


        phonetic_array[k] = _bm_expand_alternates(phonetic2)

    phonetic = '|'.join(phonetic_array)
    if strip:
        phonetic = _bm_normalize_lang_attrs(phonetic, True)

    if '|' in phonetic:
        phonetic = '(' + _bm_remove_dupes(phonetic) + ')'

    return phonetic


def _bm_phonetic_number(phonetic):
    """Remove bracketed text from the end of a string.

    :param str phonetic: a Beider-Morse phonetic encoding
    """
    if '[' in phonetic:
        return phonetic[: phonetic.find('[')]

    return phonetic  # experimental !!!!


def _bm_expand_alternates(phonetic):
    """Expand phonetic alternates separated by |s.

    :param str phonetic: a Beider-Morse phonetic encoding
    """
    alt_start = phonetic.find('(')
    if alt_start == -1:
        return _bm_normalize_lang_attrs(phonetic, False)

    prefix = phonetic[:alt_start]
    alt_start += 1  # get past the (
    alt_end = phonetic.find(')', alt_start)
    alt_string = phonetic[alt_start:alt_end]
    alt_end += 1  # get past the )
    suffix = phonetic[alt_end:]
    alt_array = alt_string.split('|')
    result = ''

    for i in range(len(alt_array)):

        alt = alt_array[i]
        alternate = _bm_expand_alternates(prefix + alt + suffix)
        if alternate != '' and alternate != '[0]':
            if result != '':
                result += '|'
            result += alternate

    return result


def _bm_pnums_with_leading_space(phonetic):
    """Join prefixes & suffixes in cases of alternate phonetic values.

    :param str phonetic: a Beider-Morse phonetic encoding
    """
    alt_start = phonetic.find('(')
    if alt_start == -1:
        return ' ' + _bm_phonetic_number(phonetic)

    prefix = phonetic[:alt_start]
    alt_start += 1  # get past the (
    alt_end = phonetic.find(')', alt_start)
    alt_string = phonetic[alt_start:alt_end]
    alt_end += 1  # get past the )
    suffix = phonetic[alt_end:]
    alt_array = alt_string.split('|')
    result = ''
    for alt in alt_array:
        result += _bm_pnums_with_leading_space(prefix + alt + suffix)

    return result


def _bm_phonetic_numbers(phonetic):
    """Prepare & join phonetic numbers.

    Split phonetic value on '-', run through _bm_pnums_with_leading_space,
    and join with ' '

    :param str phonetic: a Beider-Morse phonetic encoding
    """
    phonetic_array = phonetic.split('-')  # for names with spaces in them
    result = ' '.join(
        [_bm_pnums_with_leading_space(i)[1:] for i in phonetic_array]
    )
    return result


def _bm_remove_dupes(phonetic):
    """Remove duplicates from a phonetic encoding list.

    :param str phonetic: a Beider-Morse phonetic encoding
    """
    alt_string = phonetic
    alt_array = alt_string.split('|')

    result = '|'
    for i in range(len(alt_array)):

        alt = alt_array[i]
        if alt and '|' + alt + '|' not in result:
            result += alt + '|'

    return result[1:-1]  # remove leading and trailing |


def _bm_normalize_lang_attrs(text, strip):
    """Remove embedded bracketed attributes.

    This (potentially) bitwise-ands bracketed attributes together and adds to
    the end.
    This is applied to a single alternative at a time -- not to a
    parenthisized list.
    It removes all embedded bracketed attributes, logically-ands them together,
    and places them at the end.
    However if strip is true, this can indeed remove embedded bracketed
    attributes from a parenthesized list.

    :param str text: a Beider-Morse phonetic encoding (in progress)
    :param bool strip: remove the bracketed attributes (and throw away)
    """
    uninitialized = -1  # all 1's
    attrib = uninitialized
    while '[' in text:
        bracket_start = text.find('[')
        bracket_end = text.find(']', bracket_start)
        if bracket_end == -1:
            raise ValueError(
                'No closing square bracket: text=('
                + text
                + ') strip=('
                + text_type(strip)
                + ')'
            )
        attrib &= int(text[bracket_start + 1 : bracket_end])
        text = text[:bracket_start] + text[bracket_end + 1 :]

    if attrib == uninitialized or strip:
        return text
    elif attrib == 0:
        # means that the attributes were incompatible and there is no
        # alternative here
        return '[0]'
    return text + '[' + str(attrib) + ']'


def _bm_apply_rule_if_compat(phonetic, target, language_arg):
    """Apply a phonetic regex if compatible.

    tests for compatible language rules

    to do so, apply the rule, expand the results, and detect alternatives with
        incompatible attributes

    then drop each alternative that has incompatible attributes and keep those
        that are compatible

    if there are no compatible alternatives left, return false

    otherwise return the compatible alternatives

    apply the rule

    :param str phonetic: the Beider-Morse phonetic encoding (so far)
    :param str target: a proposed addition to the phonetic encoding
    :param int language_arg: an integer representing the target language of
        the phonetic encoding
    """
    candidate = phonetic + target
    if '[' not in candidate:  # no attributes so we need test no further
        return candidate

    # expand the result, converting incompatible attributes to [0]
    candidate = _bm_expand_alternates(candidate)
    candidate_array = candidate.split('|')

    # drop each alternative that has incompatible attributes
    candidate = ''
    found = False

    for i in range(len(candidate_array)):

        this_candidate = candidate_array[i]
        if language_arg != 1:
            this_candidate = _bm_normalize_lang_attrs(
                this_candidate + '[' + str(language_arg) + ']', False
            )
        if this_candidate != '[0]':
            found = True
            if candidate:
                candidate += '|'
            candidate += this_candidate

    # return false if no compatible alternatives remain
    if not found:
        return None

    # return the result of applying the rule
    if '|' in candidate:
        candidate = '(' + candidate + ')'
    return candidate


def _bm_language_index_from_code(code, name_mode):
    """Return the index value for a language code.

    This returns l_any if more than one code is specified or the code is out
    of bounds.

    :param int code: the language code to interpret
    :param str name_mode: the name mode of the algorithm: 'gen' (default),
                'ash' (Ashkenazi), or 'sep' (Sephardic)
    """
    if code < 1 or code > sum(
        _LANG_DICT[_] for _ in BMDATA[name_mode]['languages']

    ):  # code out of range
        return L_ANY
    if (code & (code - 1)) != 0:  # choice was more than one language; use any
        return L_ANY
    return code


def bmpm(

    word,

    language_arg=0,

    name_mode='gen',

    match_mode='approx',

    concat=False,

    filter_langs=False,

):
    """Return the Beider-Morse Phonetic Matching encoding(s) of a term.

    The Beider-Morse Phonetic Matching algorithm is described in
    :cite:`Beider:2008`.
    The reference implementation is licensed under GPLv3.

    :param str word: the word to transform
    :param str language_arg: the language of the term; supported values
        include:

            - 'any'
            - 'arabic'
            - 'cyrillic'
            - 'czech'
            - 'dutch'
            - 'english'
            - 'french'
            - 'german'
            - 'greek'
            - 'greeklatin'
            - 'hebrew'
            - 'hungarian'
            - 'italian'
            - 'latvian'
            - 'polish'
            - 'portuguese'
            - 'romanian'
            - 'russian'
            - 'spanish'
            - 'turkish'

    :param str name_mode: the name mode of the algorithm:

            - 'gen' -- general (default)
            - 'ash' -- Ashkenazi
            - 'sep' -- Sephardic

    :param str match_mode: matching mode: 'approx' or 'exact'
    :param bool concat: concatenation mode
    :param bool filter_langs: filter out incompatible languages
    :returns: the BMPM value(s)
    :rtype: tuple

    >>> bmpm('Christopher')
    'xrQstopir xrQstYpir xristopir xristYpir xrQstofir xrQstYfir xristofir
    xristYfir xristopi xritopir xritopi xristofi xritofir xritofi tzristopir
    tzristofir zristopir zristopi zritopir zritopi zristofir zristofi zritofir
    zritofi'
    >>> bmpm('Niall')
    'nial niol'
    >>> bmpm('Smith')
    'zmit'
    >>> bmpm('Schmidt')
    'zmit stzmit'

    >>> bmpm('Christopher', language_arg='German')
    'xrQstopir xrQstYpir xristopir xristYpir xrQstofir xrQstYfir xristofir
    xristYfir'
    >>> bmpm('Christopher', language_arg='English')
    'tzristofir tzrQstofir tzristafir tzrQstafir xristofir xrQstofir xristafir
    xrQstafir'
    >>> bmpm('Christopher', language_arg='German', name_mode='ash')
    'xrQstopir xrQstYpir xristopir xristYpir xrQstofir xrQstYfir xristofir
    xristYfir'

    >>> bmpm('Christopher', language_arg='German', match_mode='exact')
    'xriStopher xriStofer xristopher xristofer'
    """
    word = normalize('NFC', text_type(word.strip().lower()))

    name_mode = name_mode.strip().lower()[:3]
    if name_mode not in {'ash', 'sep', 'gen'}:
        name_mode = 'gen'

    if match_mode != 'exact':
        match_mode = 'approx'

    # Translate the supplied language_arg value into an integer representing
    # a set of languages
    all_langs = sum(_LANG_DICT[_] for _ in BMDATA[name_mode]['languages']) - 1
    lang_choices = 0
    if isinstance(language_arg, (int, float, long)):

        lang_choices = int(language_arg)
    elif language_arg != '' and isinstance(language_arg, (text_type, str)):
        for lang in text_type(language_arg).lower().split(','):
            if lang in _LANG_DICT and (_LANG_DICT[lang] & all_langs):
                lang_choices += _LANG_DICT[lang]
            elif not filter_langs:
                raise ValueError(
                    'Unknown \'' + name_mode + '\' language: \'' + lang + '\''
                )

    # Language choices are either all incompatible with the name mode or
    # no choices were given, so try to autodetect
    if lang_choices == 0:
        language_arg = _bm_language(word, name_mode)
    else:
        language_arg = lang_choices
    language_arg2 = _bm_language_index_from_code(language_arg, name_mode)

    rules = BMDATA[name_mode]['rules'][language_arg2]
    final_rules1 = BMDATA[name_mode][match_mode]['common']
    final_rules2 = BMDATA[name_mode][match_mode][language_arg2]

    result = _bm_phonetic(
        word,
        name_mode,
        rules,
        final_rules1,
        final_rules2,
        language_arg,
        concat,
    )
    result = _bm_phonetic_numbers(result)

    return result


if __name__ == '__main__':
    import doctest

    doctest.testmod()

chrislit / abydos

Branch — master (78a222)

abydos.phonetic._bmpm._bm_phonetic() F

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